Search Results (26)

Coral disease outbreaks have increased in frequency and extent worldwide since the 1970s, coinciding with the rapid increase in ocean warming. Summer and winter temperature-based metrics have proven effective in predicting coral disease outbreaks in seasonal coral reef regions. However, their utility is unknown in non-seasonal coral reef areas. Here, a new methodology, independent of seasonal patterns, is developed for application in both seasonal and non-seasonal coral reef regions. Percentile-based metric thresholds were defined from seasonal equivalents in the Great Barrier Reef (GBR) and tested in seasonal and non-seasonal coral reef regions of the tropical Pacific Ocean. Between new and existing methodologies, median differences of 0.00 °C (thresholds) and 0.00 °C-weeks (metrics) for Hot Snap and Cold Snap; and 0.01 °C (threshold) and −0.17 °C-weeks (metric) for Winter Condition were observed among reef pixels of the GBR. The new methodology shows strong consistency with the existing tools used for seasonal regions (e.g., R² = 0.811–0.903; GBR case studies). Comparisons of the new metrics with disease observations were constrained by the limited availability of disease data; however, the comparisons undertaken suggest predictive capability in non-seasonal regions. To establish robust correlations, further direct comparisons of the new metrics with disease data across various non-seasonal regions and timeframes are essential. With ocean warming projected to persist in the coming decades, improving the predictive tools used to assess ecological impacts is necessary to support effective coral reef management. Full article

The recent widespread and recurrent coral bleaching events over the Great Barrier Reef, the largest coral reef system on Earth and a hotspot of marine biodiversity, are a reminder of the vulnerability of reef ecosystems to human activities and a warming world. Protection of the Great Barrier Reef and similar reef ecosystems across Oceania requires a better understanding of environmental and socio-economic pressures, as well as the development of integrated management strategies. The rapid expansion of Earth Observation technologies and data has greatly advanced our capability to map and monitor reef habitats, ecological processing and exposure risk, providing spatially rich data essential to support and evaluate management and conservation strategies. However, these technologies are proportionally still under-utilized, and it is important to synthesise remote-sensing-derived tools and methods currently available for mapping reef ecosystems in Oceania to facilitate their intake in coral reefs studies. Publications in this Special Issue contribute toward filling this gap and explore recent advances in remote sensing of the Great Barrier Reef and other reef ecosystems in Oceania, from novel methodological approaches (sensors, algorithm development and improved thematic classification) to applications for environmental monitoring and management. Full article

Coral reefs and their associated marine communities are increasingly threatened by anthropogenic climate change. A key step in the management of climate threats is an efficient and accurate end-to-end system of coral monitoring that can be generally applied to shallow water reefs. Here, we used RGB drone-based imagery and a deep learning algorithm to develop a system of classifying bleached and unbleached corals. Imagery was collected five times across one year, between November 2018 and November 2019, to assess coral bleaching and potential recovery around Lord Howe Island, Australia, using object-based image analysis. This training mask was used to develop a large training dataset, and an mRES-uNet architecture was chosen for automated segmentation. Unbleached coral classifications achieved a precision of 0.96, a recall of 0.92, and a Jaccard index of 0.89, while bleached corals achieved 0.28 precision, 0.58 recall, and a 0.23 Jaccard index score. Subsequently, methods were further refined by creating bleached coral objects (>16 pixels total) using the neural network classifications of bleached coral pixels, to minimize pixel error and count bleached coral colonies. This method achieved a prediction precision of 0.76 in imagery regions with >2000 bleached corals present, and 0.58 when run on an entire orthomosaic image. Bleached corals accounted for the largest percentage of the study area in September 2019 (6.98%), and were also significantly present in March (2.21%). Unbleached corals were the least dominant in March (28.24%), but generally accounted for ~50% of imagery across other months. Overall, we demonstrate that drone-based RGB imagery, combined with artificial intelligence, is an effective method of coral reef monitoring, providing accurate and high-resolution information on shallow reef environments in a cost-effective manner. Full article

Seagrass beds provide a range of ecosystem services but are at risk from anthropogenic pressures. While recent progress has been made, the distribution and condition of South Pacific seagrass is relatively poorly known and selecting an appropriate approach for mapping it is challenging. A variety of remote sensing tools are available for this purpose and here we develop a mapping toolbox and associated decision tree tailored to the South Pacific context. The decision tree considers the scale at which data are needed, the reason that monitoring is required, the finances available, technical skills of the monitoring team, data resolution, site safety/accessibility and whether seagrass is predominantly intertidal or subtidal. Satellite mapping is recommended for monitoring at the national and regional scale, with associated ground-reference data where possible but without if time and funds are limiting. At the local scale, satellite, remotely piloted aircraft (RPA), kites, underwater camera systems and in situ surveys are all recommended. In the special cases of community-based initiatives and emergency response monitoring, in situ or satellite/RPA are recommended, respectively. For other types of monitoring the primary driver is funding, with in situ, kite and satellite recommended when finances are limited and satellite, underwater camera, RPA or kites otherwise, dependent on specific circumstances. The tools can be used individually or in combination, though caution is recommended when combining tools due to data comparability. Full article

In January 2013, tropical cyclone Oswald caused widespread flooding in the North-East coast of Australia, and large and highly episodic inputs into Princess Charlotte Bay (PCB, northern Great Barrier Reef). Freshwater outflows from the Normanby and Kennedy rivers, the two main rivers draining the adjacent catchments, resulted in drastic changes in physical, biogeochemical and optical properties within PCB. On 31 January, 2 days after the peak riverine discharge from the Normanby river, nutrients and dissolved organic matter contents peaked under the influence of large outflows from the Kennedy river into the western section of the bay (5.8 μM for dissolved inorganic nitrogen, 6.9 g m⁻³ for dissolved organic carbon and 6.1 m⁻¹ for the colored dissolved organic matter absorption coefficient at 412 nm). In the eastern section of the bay, the situation appeared more ‘mixed’, with a suspended solids concentration reaching 23.1 g m⁻³ close to the Normanby river mouth. The main phytoplankton bloom occurred in the transition zone between the Kennedy and Normanby flood plumes, and was dominated by diatoms with a chlorophyll a concentration reaching 14.6 mg m⁻³. This study highlights the need to better describe the critical spatial and temporal scales of variability of key biogeochemical and optical properties after a major flood event. The data collected is key to improve the accuracy of ocean color remote sensing algorithms and regional biogeochemical budgets following highly episodic inputs. Full article

Very shallow coral reefs (<5 m deep) are naturally exposed to strong sea surface temperature variations, UV radiation and other stressors exacerbated by climate change, raising great concern over their future. As such, accurate and ecologically informative coral reef maps are fundamental for their management and conservation. Since traditional mapping and monitoring methods fall short in very shallow habitats, shallow reefs are increasingly mapped with Unmanned Aerial Vehicles (UAVs). UAV imagery is commonly processed with Structure-from-Motion (SfM) to create orthomosaics and Digital Elevation Models (DEMs) spanning several hundred metres. Techniques to convert these SfM products into ecologically relevant habitat maps are still relatively underdeveloped. Here, we demonstrate that incorporating geomorphometric variables (derived from the DEM) in addition to spectral information (derived from the orthomosaic) can greatly enhance the accuracy of automatic habitat classification. Therefore, we mapped three very shallow reef areas off KAUST on the Saudi Arabian Red Sea coast with an RTK-ready UAV. Imagery was processed with SfM and classified through object-based image analysis (OBIA). Within our OBIA workflow, we observed overall accuracy increases of up to 11% when training a Random Forest classifier on both spectral and geomorphometric variables as opposed to traditional methods that only use spectral information. Our work highlights the potential of incorporating a UAV’s DEM in OBIA for benthic habitat mapping, a promising but still scarcely exploited asset. Full article

Distinct absorption peaks, with maxima at around 328 nm and a shoulder at 360 nm, were observed in the UV region of the absorption spectra for both the particulate and dissolved fractions of water samples collected in Keppel Bay (NE Australia) during the presence of sporadic Trichodesmium colonies. The largest absorption coefficients for these peaks were observed in samples collected in the near-surface waters (top 2–3 cm). Values approximately 3.5–6 times greater for a_CDOM(328) and 13–36 times greater for a_p(328) were observed in the near-surface samples compared to those collected from the top 20 cm of the water column at the same sites. Similar UV-absorption peaks observed in other studies have been attributed to the presence of mycosporine-like amino acids (MAAs). Increased UV absorption can affect both the magnitude of the absorption coefficients in the blue end of the visible region and the spectral slope of the exponential model commonly used to describe the CDOM absorption coefficient. This, in turn, can significantly affect the accuracy of satellite retrieved estimates of ocean colour products related to CDOM and particulate absorption coefficients. In tropical waters where Trichodesmium blooms are prevalent, regional ocean colour algorithms need to be developed using in situ bio-optical measurements from both the UV and visible regions of the spectra. Full article

Remote sensing of ocean colour has been fundamental to the synoptic-scale monitoring of marine water quality in the Great Barrier Reef (GBR). However, ocean colour sensors onboard low orbit satellites, such as the Sentinel-3 constellation, have insufficient revisit capability to fully resolve diurnal variability in highly dynamic coastal environments. To overcome this limitation, this work presents a physics-based coastal ocean colour algorithm for the Advanced Himawari Imager onboard the Himawari-8 geostationary satellite. Despite being designed for meteorological applications, Himawari-8 offers the opportunity to estimate ocean colour features every 10 min, in four broad visible and near-infrared spectral bands, and at 1 km² spatial resolution. Coupled ocean–atmosphere radiative transfer simulations of the Himawari-8 bands were carried out for a realistic range of in-water and atmospheric optical properties of the GBR and for a wide range of solar and observation geometries. The simulated data were used to develop an inverse model based on artificial neural network techniques to estimate total suspended solids (TSS) concentrations directly from the Himawari-8 top-of-atmosphere spectral reflectance observations. The algorithm was validated with concurrent in situ data across the coastal GBR and its detection limits were assessed. TSS retrievals presented relative errors up to 75% and absolute errors of 2 mg L⁻¹ within the validation range of 0.14 to 24 mg L⁻¹, with a detection limit of 0.25 mg L⁻¹. We discuss potential applications of Himawari-8 diurnal TSS products for improved monitoring and management of water quality in the GBR. Full article

The bio-optical properties of coral reef waters were examined across coral reef ecosystems not influenced by land-derived run-off, in the Great Barrier Reef lagoon (Heron Island) and the Coral Sea (the Coringa-Herald and Lihou Reefs). The aim was to determine whether the absorption properties, the concentration-specific absorption properties, and the phytoplankton and non-algal pigmented particle (NAP) absorption concentrations varied from the ocean waters flushing onto the reef at high tide to those waters on the reef or flushing off the reef at low tide. The optical and biogeochemical properties of on-reef waters systematically differed from the surrounding ocean waters. The chl a concentration values varied up to 7-fold and the NAP concentrations up to 29-fold; for the reef samples, the chl a values were on average 2 to 3 times lower than for the oceans whilst the NAP values were slightly higher on the reefs. The spectral absorption values of the chl a, NAP, and colored dissolved organic matter (CDOM) varied up to 6-fold for reef waters and up to 15-fold for ocean waters. The spectral absorption for chl a was up to 3-fold lower on the reef waters, the absorption by the CDOM was up to 2-fold higher and the NAP absorption was 1.6-fold higher on the reef waters. The concentration-specific absorption coefficients for chl a and NAP varied up to 9-fold in reef waters and up to 30-fold in ocean waters. In the case of Heron Island and Coringa-Herald cays, this concentration-specific absorption was on average 1.3 to 1.7-fold higher for chl a and up to 2-fold lower for NAP on the reefs. The Lihou Reef measurements were more ambiguous between the reef waters and ocean waters due to the complex nature and size of this reef. Based on our results, the assumption that the optical properties of on-reef waters and the adjacent ocean waters are the same was shown to be invalid. Ocean waters flowing on to the reef are higher in phytoplankton, whilst waters on the reef or flowing off the reefs are higher in CDOM and NAP. We found differences in the pico,- nano-, and microplankton distributions as well as in the ratios of photosynthetic to photoprotective pigments. The variability in the bio-optical properties between the reef waters and adjacent ocean waters has implications for the estimations of sunlight absorption along the water column, the UV penetration depth, the temperature distributions, and the nutrient and carbon fluxes in coral reef ecosystems. As Earth observation algorithms require proper parameterization for the water column effects when estimating benthic cover, the actual optical properties need to be used. These results will improve the use of Earth observation to systematically map the differences in the water quality between reefs and the adjacent ocean. Full article

Seagrass meadows are a key ecosystem of the Great Barrier Reef World Heritage Area, providing one of the natural heritage attributes underpinning the reef’s outstanding universal value. We reviewed approaches employed to date to create maps of seagrass meadows in the optically complex waters of the Great Barrier Reef and explored enhanced mapping approaches with a focus on emerging technologies, and key considerations for future mapping. Our review showed that field-based mapping of seagrass has traditionally been the most common approach in the GBRWHA, with few attempts to adopt remote sensing approaches and emerging technologies. Using a series of case studies to harness the power of machine- and deep-learning, we mapped seagrass cover with PlanetScope and UAV-captured imagery in a variety of settings. Using a machine-learning pixel-based classification coupled with a bootstrapping process, we were able to significantly improve maps of seagrass, particularly in low cover, fragmented and complex habitats. We also used deep-learning models to derive enhanced maps from UAV imagery. Combined, these lessons and emerging technologies show that more accurate and efficient seagrass mapping approaches are possible, producing maps of higher confidence for users and enabling the upscaling of seagrass mapping into the future. Full article

The use of ocean colour classification algorithms, linked to water quality gradients, can be a useful tool for mapping river plumes in both tropical and temperate systems. This approach has been applied in operational water quality programs in the Great Barrier Reef to map river plumes and assess trends in marine water composition and ecosystem health during flood periods. In this study, we used the Forel–Ule colour classification algorithm for Sentinel-3 OLCI imagery in an automated process to map monthly, annual and long-term plume movement in the temperate coastal system of Liverpool Bay (UK). We compared monthly river plume extent to the river flow and in situ water quality data between 2017–2020. The results showed a strong positive correlation (Spearman’s rho = 0.68) between the river plume extent and the river flow and a strong link between the FUI defined waterbodies and nutrients, SPM, turbidity and salinity, hence the potential of the Forel–Ule index to act as a proxy for water quality in the temperate Liverpool Bay water. The paper discusses how the Forel–Ule index could be used in operational water quality programs to better understand river plumes and the land-based inputs to the coastal zones in UK waters, drawing parallels with methods that have been developed in the GBR and Citclops project. Overall, this paper provides the first insight into the systematic long-term river plume mapping in UK coastal waters using a fast, cost-effective, and reproducible workflow. The study created a novel water assessment typology based on the common physical, chemical and biological ocean colour properties captured in the Forel–Ule index, which could replace the more traditional eutrophication assessment regions centred around strict geographic and political boundaries. Additionally, the Forel–Ule assessment typology is particularly important since it identifies areas of the greatest impact from the land-based loads into the marine environment, and thus potential risks to vulnerable ecosystems. Full article

For many years, local communities have expressed concerns that turbid plume waters from the Fly River in Papua New Guinea may potentially deliver mine-derived contaminants to the Torres Strait, an ecologically and culturally unique area north of the Australian mainland. Information on suspended sediment transport and turbidity patterns are needed in this data-limited region to identify and manage downstream ecosystems that may be at risk of exposure from the Fly River runoff. This study used MODIS satellite time series and a colour-classification approach to map optical water types around the data-poor Gulf of Papua and Torres Strait region. The satellite data were supported by field data, including salinity and suspended sediment measurements, and used together in qualitative water quality assessments to evaluate the habitats that are likely exposed to Fly River discharge and/or derived sediments. It showed that the Fly River influence in the Torres Strait region is largely limited to the north-east corner of the Torres Strait. The drivers of turbidity vary between locations, and it is impossible to fully separate direct riverine plume influence from wave and tidally driven sediment resuspension in the satellite maps. However, results indicate that coastal habitats located as far east as Bramble Cay and west to Boigu Island are located in an area that is most likely exposed to the Fly River discharge within the region, directly or through sediment resuspension. The area that is the most likely exposed is a relatively small proportion of the Torres Strait region, but encompasses habitats of high ecological importance, including coral reefs and seagrass meadows. Satellite data showed that the period of highest risk of exposure was during the south-east trade wind season and complemented recent model simulations in the region over larger spatial and temporal frames. This study did not evaluate transboundary pollution or the ecological impact on local marine resources, but other recent studies suggest it is likely to be limited. However, this study did provide long-term, extensive but qualitative, baseline information needed to inform future ecological risk mapping and to support decision making about management priorities in the region. This is important for ensuring the protection of the Torres Strait ecosystems, given their importance to Torres Strait communities and turtle and dugong populations, and the Torres Strait’s connectivity with the Great Barrier Reef Marine Park. Full article

The Ningaloo Reef, Australia’s longest fringing reef, is uniquely positioned in the NW region of the continent, with clear, oligotrophic waters, relatively low human impacts, and a high level of protection through the World Heritage Site and its marine park status. Non-invasive optical sensors, which seamlessly derive bathymetry and bottom reflectance, are ideally suited for mapping and monitoring shallow reefs such as Ningaloo. Using an existing airborne hyperspectral survey, we developed a new, geomorphic layer for the reef for depths down to 20 m, through an object-oriented classification that combines topography and benthic cover. We demonstrate the classification approach using three focus areas in the northern region of the Muiron Islands, the central part around Point Maud, and Gnaraloo Bay in the south. Topographic mapping combined aspect, slope, and depth into 18 classes and, unsurprisingly, allocated much of the area into shallow, flat lagoons, and highlighted narrow, deeper channels that facilitate water circulation. There were five distinct geomorphic classes of coral-algal mosaics in different topographic settings. Our classifications provide a useful baseline for stratifying ecological field surveys, designing monitoring programmes, and assessing reef resilience from current and future threats. Full article

Australia’s Great Barrier Reef (GBR) is a globally unique and precious national resource; however, the geomorphic and benthic composition and the extent of coral habitat per reef are greatly understudied. However, this is critical to understand the spatial extent of disturbance impacts and recovery potential. This study characterizes and quantifies coral habitat based on depth, geomorphic and benthic composition maps of more than 2164 shallow offshore GBR reefs. The mapping approach combined a Sentinel-2 satellite surface reflectance image mosaic and derived depth, wave climate, reef slope and field data in a random-forest machine learning and object-based protocol. Area calculations, for the first time, incorporated the 3D characteristic of the reef surface above 20 m. Geomorphic zonation maps (0–20 m) provided a reef extent estimate of 28,261 km² (a 31% increase to current estimates), while benthic composition maps (0–10 m) estimated that ~10,600 km² of reef area (~57% of shallow offshore reef area) was covered by hard substrate suitable for coral growth, the first estimate of potential coral habitat based on substrate availability. Our high-resolution maps provide valuable information for future monitoring and ecological modeling studies and constitute key tools for supporting the management, conservation and restoration efforts of the GBR. Full article

Increasingly intense marine heatwaves threaten the persistence of many marine ecosystems. Heat stress-mediated episodes of mass coral bleaching have led to catastrophic coral mortality globally. Remotely monitoring and forecasting such biotic responses to heat stress is key for effective marine ecosystem management. The Degree Heating Week (DHW) metric, designed to monitor coral bleaching risk, reflects the duration and intensity of heat stress events and is computed by accumulating SST anomalies (HotSpot) relative to a stress threshold over a 12-week moving window. Despite significant improvements in the underlying SST datasets, corresponding revisions of the HotSpot threshold and accumulation window are still lacking. Here, we fine-tune the operational DHW algorithm to optimise coral bleaching predictions using the 5 km satellite-based SSTs (CoralTemp v3.1) and a global coral bleaching dataset (37,871 observations, National Oceanic and Atmospheric Administration). After developing 234 test DHW algorithms with different combinations of the HotSpot threshold and accumulation window, we compared their bleaching prediction ability using spatiotemporal Bayesian hierarchical models and sensitivity–specificity analyses. Peak DHW performance was reached using HotSpot thresholds less than or equal to the maximum of monthly means SST climatology (MMM) and accumulation windows of 4–8 weeks. This new configuration correctly predicted up to an additional 310 bleaching observations globally compared to the operational DHW algorithm, an improved hit rate of 7.9%. Given the detrimental impacts of marine heatwaves across ecosystems, heat stress algorithms could also be fine-tuned for other biological systems, improving scientific accuracy, and enabling ecosystem governance. Full article